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AI Security Code Examples

This repository contains practical code examples for implementing AI security measures against prompt injection attacks and other LLM vulnerabilities.

Repository Structure

ai-security-code-examples/
├── traditional-security/          # Traditional security approaches
├── ai-aware-security/             # AI-specific security implementations
├── promptfoo-configs/             # Promptfoo configuration examples
├── defensive-prompts/             # Defensive prompt architectures
├── monitoring-systems/            # Real-time monitoring implementations
├── incident-response/             # Automated incident response
├── metrics-frameworks/            # Security metrics and ROI calculations
└── deployment-scripts/            # Quick deployment automation

Quick Start

  1. Install Dependencies

    npm install -g promptfoo
pip install -r requirements.txt

  2. Run Security Assessment

    cd promptfoo-configs
promptfoo redteam run --config comprehensive-security.yaml

  3. Deploy Basic Security

    cd deployment-scripts
./emergency-deployment.sh

Key Features

  • ✅ Complete OWASP LLM Top 10 coverage
  • ✅ Traditional vs AI-aware security comparisons
  • ✅ Production-ready Promptfoo configurations
  • ✅ Defensive prompt architectures
  • ✅ Real-time monitoring systems
  • ✅ Automated incident response
  • ✅ ROI and metrics frameworks

Documentation

Each directory contains detailed README files with:

  • Implementation guides
  • Code explanations
  • Usage examples
  • Best practices

License

MIT License - See LICENSE file for details

Contributing

Pull requests welcome! Please read CONTRIBUTING.md for guidelines.